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Here's our August 20, 2024 release!
Individual chapters and updated slides are below;
Here is a single pdf of Aug 20, 2024 book!
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Feel free to use the draft chapters and slides in your classes, print it out, whatever, the resulting feedback we get from you makes the book better!
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Typos and comments are very welcome (just email slp3edbugs@gmail.com
and let us know the date on the draft)!
(Don't bother reporting missing refs due to cross-chapter cross-reference problems in the indvidual chapter pdfs, those are fixed in the full book draft)
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Gratitude! We've put up a list here of the amazing people who have sent so many fantastic suggestions and bug-fixes for improving the book.
We are really grateful to all of you for your help, the book would not be possible without you!
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How to cite the book:
Daniel Jurafsky and James H. Martin. 2024. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models, 3rd edition. Online manuscript released August 20, 2024. https://web.stanford.edu/~jurafsky/slp3.
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A bib entry for the book is here.
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When will the book be finished? Don't ask.
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If you need the previous Feb 2024 draft chapters,
they are here;
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Chapter |
Slides |
| Part I: Fundamental Algorithms |
1: | Introduction |
2: |
Regular Expressions, Tokenization, Edit Distance |
2: Text Processing
[pptx]
[pdf]
2: Edit Distance
[pptx]
[pdf]
|
3: |
N-gram Language Models |
3: [pptx]
[pdf]
|
4: |
Naive Bayes, Text Classification, and Sentiment |
4: [pptx]
[pdf]
|
5: |
Logistic Regression |
5: [pptx]
[pdf]
|
6: |
Vector Semantics and Embeddings |
6: [pptx]
[pdf]
|
7: |
Neural Networks
|
7: [pptx] [pdf]
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8: |
RNNs and LSTMs |
9: |
Transformers
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9: [pptx]
[pdf]
|
10: |
Large Language Models |
10: [pptx]
[pdf]
| 11: | Masked Language Models |
12: |
Model Alignment, Prompting, and In-Context Learning |
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| Part II: NLP Applications |
13: | Machine Translation |
14: | Question Answering, Information Retrieval, and RAG |
15: | Chatbots and Dialogue Systems |
15 [pptx]
[pdf]
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16: | Automatic Speech Recognition and Text-to-Speech |
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| Part III: Annotating Linguistic Structure |
17: |
Sequence Labeling for Parts of Speech and Named Entities |
17: (Intro only) [pptx] [pdf]
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18: | Context-Free Grammars and Constituency Parsing |
19: | Dependency Parsing |
20: | Information Extraction: Relations, Events, and Time |
21: | Semantic Role Labeling and Argument Structure |
22: | Lexicons for Sentiment, Affect, and Connotation |
23: | Coreference Resolution and Entity Linking |
24: | Discourse Coherence |
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| Appendix Chapters (will be just on the web) |
A: | Hidden Markov Models |
B: | Spelling Correction and the Noisy Channel |
C: | Statistical Constituency Parsing |
D: | Context-Free Grammars |
E: | Combinatory Categorial Grammar |
F: | Logical Representations of Sentence Meaning |
G: | Word Senses and WordNet |
H: | Phonetics |
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